Manufacturers are increasingly utilizing machine tools that are self-aware – they perceive their own states and the state of the surrounding environment – and are able to make decisions related to machine activity processes. This is called intelligent machining, and through this course students will receive a primer on its background, tools and related terminology.
Learn how the integration of smart sensors and controls are helping to improve productivity. You’ll be exposed to various sensors and sensing techniques, process control strategies, and open architecture systems that can be leveraged to enable intelligent machining. This course will prepare you to contribute to the implementation of intelligent machining projects.
Main concepts of this course will be delivered through lectures, readings, discussions and various videos.
This is the fifth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal.
To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA

Taught By

Rahul Rai

Transcript

[MUSIC] Welcome to module four, The Future of Intelligent Machining. At the end of this module, you will be able to explain why intelligent machining is an integral part of manufacturing process improvement. Describe the roles of IIOT, or Industrial Internet of Things, intelligent machining and big data in a digital manufacturing enterprise. And discuss how intelligent machining is going to change the future of digital manufacturing. [MUSIC] This lesson will focus how digital manufacturing is revolutionizing the intelligent machining paradigm. Several examples of intelligent machining in distributed setting will be presented to indicate future possibilities. Vision technology combines high-definition cameras with software to identify complex geometric objects in variable lighting conditions. The advances in vision technology assist in creating intelligent manufacturing solutions, for example robotic bin picking. Here we see two different geometric objects being recognized and picked by a robotic end effector and placed on a conveyor. The system identifies defective parts that are non-compliant, and only allows conforming parts to move on to the next phase of the manufacturing process. The robot integration reduces the operator involvement and allows for a safer operating conditions. Some other future possibilities include, connected machines in manifacturing softload, connected factories and digitally-enabled supply chains. At machine level, the data collected during condition monitoring of a machine can be shared with other industry partners to help them identify potential mechanical issues leading to machine failure. In the future, remote operation of machines will also become feasible and easy to handle with less human intervention. Intelligent machining will enable the production to become more flexible and first, shrink the time to market for next-generation products. Using intelligent machining, Industrial Internet of Things, and big data, small-scale enterprises will adopt quickly to newer technologies and become more competitive. Intelligent machining, when combined with the power of Industrial Internet of Things or IIoTs can result in connected machines within a factory. Which can further be expanded to connect different factories, and a truly digitally-enabled supply chain. This connected enterprise can be a huge enabler for the realization of the digital trend. Which is generating, sharing, and utilizing data and information at all stages of the product life cycle, from ideation to disposal, throughout the supply chain. Thereby enabling stakeholders to make smarter decisions in real time.

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